Public health insurance coverage in India before and after PM-JAY: repeated cross-sectional analysis of nationally representative survey data
Introduction The provision of non-contributory public health insurance (NPHI) to marginalised populations is a critical step along the path to universal health coverage. We aimed to assess the extent to which Ayushman Bharat-Pradhan Mantri Jan Arogya Yojana (PM-JAY)—potentially, the world’s largest...
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| Format: | Article |
| Language: | English |
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BMJ Publishing Group
2023-08-01
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| Series: | BMJ Global Health |
| Online Access: | https://gh.bmj.com/content/8/8/e012725.full |
| _version_ | 1827854785930330112 |
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| author | Sanjay K Mohanty Fabrice Kämpfen Jürgen Maurer Ashish Kumar Upadhyay Suraj Maiti Radhe Shyam Mishra Owen O'Donnell |
| author_facet | Sanjay K Mohanty Fabrice Kämpfen Jürgen Maurer Ashish Kumar Upadhyay Suraj Maiti Radhe Shyam Mishra Owen O'Donnell |
| author_sort | Sanjay K Mohanty |
| collection | DOAJ |
| description | Introduction The provision of non-contributory public health insurance (NPHI) to marginalised populations is a critical step along the path to universal health coverage. We aimed to assess the extent to which Ayushman Bharat-Pradhan Mantri Jan Arogya Yojana (PM-JAY)—potentially, the world’s largest NPHI programme—has succeeded in raising health insurance coverage of the poorest two-fifths of the population of India.Methods We used nationally representative data from the National Family Health Survey on 633 699 and 601 509 households in 2015–2016 (pre-PM-JAY) and 2019–2021 (mostly, post PM-JAY), respectively. We stratified by urban/rural and estimated NPHI coverage nationally, and by state, district and socioeconomic categories. We decomposed coverage variance between states, districts, and households and measured socioeconomic inequality in coverage. For Uttar Pradesh, we tested whether coverage increased most in districts where PM-JAY had been implemented before the second survey and whether coverage increased most for targeted poorer households in these districts.Results We estimated that NPHI coverage increased by 11.7 percentage points (pp) (95% CI 11.0% to 12.4%) and 8.0 pp (95% CI 7.3% to 8.7%) in rural and urban India, respectively. In rural areas, coverage increased most for targeted households and pro-rich inequality decreased. Geographical inequalities in coverage narrowed. Coverage did not increase more in states that implemented PM-JAY. In Uttar Pradesh, the coverage increase was larger by 3.4 pp (95% CI 0.9% to 6.0%) and 4.2 pp (95% CI 1.2% to 7.1%) in rural and urban areas, respectively, in districts exposed to PM-JAY and the increase was 3.5 pp (95% CI 0.9% to 6.1%) larger for targeted households in these districts.Conclusion The introduction of PM-JAY coincided with increased public health insurance coverage and decreased inequality in coverage. But the gains cannot all be plausibly attributed to PM-JAY, and they are insufficient to reach the goal of universal coverage of the poor. |
| first_indexed | 2024-03-12T11:36:04Z |
| format | Article |
| id | doaj.art-fcd26a8d2c3a43d28a8e2d320c359d35 |
| institution | Directory Open Access Journal |
| issn | 2059-7908 |
| language | English |
| last_indexed | 2024-03-12T11:36:04Z |
| publishDate | 2023-08-01 |
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| series | BMJ Global Health |
| spelling | doaj.art-fcd26a8d2c3a43d28a8e2d320c359d352023-09-01T05:30:07ZengBMJ Publishing GroupBMJ Global Health2059-79082023-08-018810.1136/bmjgh-2023-012725Public health insurance coverage in India before and after PM-JAY: repeated cross-sectional analysis of nationally representative survey dataSanjay K Mohanty0Fabrice Kämpfen1Jürgen Maurer2Ashish Kumar Upadhyay3Suraj Maiti4Radhe Shyam Mishra5Owen O'Donnell6Department of Population and Development, International Institute for Population Sciences, Mumbai, Maharashtra, IndiaUniversity College Dublin, Dublin, IrelandDepartment of Economics and Lausanne Center for Health Economics, Behavior and Policy, Faculty of Business and Economics (HEC), University of Lausanne, Lausanne, SwitzerlandInternational Institute for Population Sciences, Mumbai, Maharashtra, IndiaInternational Institute for Population Sciences, Mumbai, Maharashtra, IndiaInternational Institute for Population Sciences, Mumbai, Maharashtra, IndiaErasmus University Rotterdam, Rotterdam, The NetherlandsIntroduction The provision of non-contributory public health insurance (NPHI) to marginalised populations is a critical step along the path to universal health coverage. We aimed to assess the extent to which Ayushman Bharat-Pradhan Mantri Jan Arogya Yojana (PM-JAY)—potentially, the world’s largest NPHI programme—has succeeded in raising health insurance coverage of the poorest two-fifths of the population of India.Methods We used nationally representative data from the National Family Health Survey on 633 699 and 601 509 households in 2015–2016 (pre-PM-JAY) and 2019–2021 (mostly, post PM-JAY), respectively. We stratified by urban/rural and estimated NPHI coverage nationally, and by state, district and socioeconomic categories. We decomposed coverage variance between states, districts, and households and measured socioeconomic inequality in coverage. For Uttar Pradesh, we tested whether coverage increased most in districts where PM-JAY had been implemented before the second survey and whether coverage increased most for targeted poorer households in these districts.Results We estimated that NPHI coverage increased by 11.7 percentage points (pp) (95% CI 11.0% to 12.4%) and 8.0 pp (95% CI 7.3% to 8.7%) in rural and urban India, respectively. In rural areas, coverage increased most for targeted households and pro-rich inequality decreased. Geographical inequalities in coverage narrowed. Coverage did not increase more in states that implemented PM-JAY. In Uttar Pradesh, the coverage increase was larger by 3.4 pp (95% CI 0.9% to 6.0%) and 4.2 pp (95% CI 1.2% to 7.1%) in rural and urban areas, respectively, in districts exposed to PM-JAY and the increase was 3.5 pp (95% CI 0.9% to 6.1%) larger for targeted households in these districts.Conclusion The introduction of PM-JAY coincided with increased public health insurance coverage and decreased inequality in coverage. But the gains cannot all be plausibly attributed to PM-JAY, and they are insufficient to reach the goal of universal coverage of the poor.https://gh.bmj.com/content/8/8/e012725.full |
| spellingShingle | Sanjay K Mohanty Fabrice Kämpfen Jürgen Maurer Ashish Kumar Upadhyay Suraj Maiti Radhe Shyam Mishra Owen O'Donnell Public health insurance coverage in India before and after PM-JAY: repeated cross-sectional analysis of nationally representative survey data BMJ Global Health |
| title | Public health insurance coverage in India before and after PM-JAY: repeated cross-sectional analysis of nationally representative survey data |
| title_full | Public health insurance coverage in India before and after PM-JAY: repeated cross-sectional analysis of nationally representative survey data |
| title_fullStr | Public health insurance coverage in India before and after PM-JAY: repeated cross-sectional analysis of nationally representative survey data |
| title_full_unstemmed | Public health insurance coverage in India before and after PM-JAY: repeated cross-sectional analysis of nationally representative survey data |
| title_short | Public health insurance coverage in India before and after PM-JAY: repeated cross-sectional analysis of nationally representative survey data |
| title_sort | public health insurance coverage in india before and after pm jay repeated cross sectional analysis of nationally representative survey data |
| url | https://gh.bmj.com/content/8/8/e012725.full |
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